Issue 8.8

Issue 8.8 is now online!

The August issue of Methods is now online!

This issue contains two Applications articles and two Open Access articles. These four papers are freely available to everyone, no subscription required.

 Paco: An R package that assesses the phylogenetic congruence, or evolutionary dependence, of two groups of interacting species using both ecological interaction networks and their phylogenetic history.

 Open MEE: Open Meta-analyst for Ecology and Evolution (Open MEE) addresses the need for advanced, easy-to-use software for meta-analysis and meta-regression.It offers a suite of advanced meta-analysis and meta-regression methods for synthesizing continuous and categorical data, including meta-regression with multiple covariates and their interactions, phylogenetic analyses, and simple missing data imputation.

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Conditional Occupancy Design Explained

Occupancy surveys are widely used in ecology to study wildlife and plant habitat use. To account for imperfect detection probability many researchers use occupancy models. But occupancy probability estimates for rare species tend to be biased because we’re unlikely to observe the animals at all and as a result, the data aren’t very informative.

In their new article – ‘Occupancy surveys with conditional replicates: An alternative sampling design for rare species‘ – Specht et al. developed a new “conditional” occupancy survey design to improve occupancy estimates for rare species, They also compare it to standard and removal occupancy study designs. In this video two of the authors, Hannah Specht and Henry Reich, explain how their new conditional occupancy survey design works. 

This video is based on the article ‘Occupancy surveys with conditional replicates: An alternative sampling design for rare species‘ by Specht et al.

 

Issue 8.7

Issue 8.7 is now online!

© Paula Matos

The July issue of Methods is now online!

This issue contains three Applications articles (one of which is Open Access) and one additional Open Access article. These four papers are freely available to everyone, no subscription required.

BioEnergeticFoodWebs: An implementation of Yodzis & Innes bio-energetic model, in the high-performance computing language Julia. This package can be used to conduct numerical experiments in a reproducible and standard way.

 Controlled plant crosses: Chambers which allow you to control pollen movement and paternity of offspring using unpollinated isolated plants and microsatellite markers for parents and their putative offspring. This system has per plant costs and efficacy superior to pollen bags used in past studies of wind-pollinated plants.

 The Global Pollen Project: The study of fossil and modern pollen assemblages provides essential information about vegetation dynamics in space and time. In this Open Access Applications article, Martin and Harvey present a new online tool – the Global Pollen Project – which aims to enable people to share and identify pollen grains. Through this, it will create an open, free and accessible reference library for pollen identification. The database currently holds information for over 1500 species, from Europe, the Americas and Asia. As the collection grows, we envision easier pollen identification, and greater use of the database for novel research on pollen morphology and other characteristics, especially when linked to other palaeoecological databases, such as Neotoma.

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Why Soft Sweeps from Standing Genetic Variation are More Likely than You May Think

We coined the term “soft sweeps” in 2005. The term has since become widely used, though not everyone uses the term in the same way. As part of the ‘How to Measure Natural Selection‘ Special Feature in Methods in Ecology and Evolution, we attempt to clarify what “soft sweep” means and doesn’t mean. For example, not every sweep from standing genetic variation is necessarily a soft sweep.
In the review paper we also show under what conditions soft sweeps are likely (e.g., high population-wide mutation rate, multi-locus selection target). Finally, we describe relevant examples in fruitflies, humans and microbes and we discuss future research directions.
The video focuses on one aspect of the paper, which is illustrated in figure 3: “Why soft sweeps from standing genetic variation are more likely than you may think.”

This video is based on the Open Access article ‘Soft sweeps and beyond: understanding the patterns and probabilities of selection footprints under rapid adaptation by Hermisson and Plennings in the ‘How to Measure Natural Selection‘ Special Feature.

 

Issue 8.6: How to Measure Natural Selection

Issue 8.6 is now online!

The April issue of Methods, which includes our latest Special Feature – ‘How to Measure Natural Selection – is now online!

Understanding how and why some individuals survive and reproduce better than others, the traits that allow them to do so, the genetic basis of those traits, and the signatures of past and present selection in patterns of variation in the genome remain at the top of the research agenda for evolutionary biology. This Special Feature – Guest Edited by Jeff Conner, John Stinchcombe and Joanna Kelley – draws together a collection of seven papers that highlight new methodological and conceptual approaches to meeting this agenda.

Three of the ‘How to Measure Natural Selection’ papers – Franklin and Morrissey, Thomson and Hadfield, and Hadfield and Thomson – clarify unresolved aspects of the literature in meaningful and important ways. Following on from this Hermisson and Pennings; Lotterhos et al.; and Villanueva‐Cañas et al. tackle the genomic results of evolution by natural selection: namely, how we can detect natural selection from genomic data? Finally, Wadgymar et al. address the issue of how much we know about the underlying loci or agents of selection.

To use the Editors’ own words, the articles in this issue “deal with how we can detect selection in a way that can be used to predict evolutionary responses, how selection affects the genome, and how selection and genetics underlie adaptive differentiation.”

All of the articles in the ‘How to Measure Natural Selection‘ Special Feature will be freely available for a limited time.
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‘Size’ and ‘Shape’ in the Measurement of Multivariate Proximity

Ordination and clustering methods are widely applied to ecological data that are non-negative (like species abundances or biomasses). These methods rely on a measure of multivariate proximity that quantifies differences between the sampling units (e.g. individuals, stations, time points), leading to results such as:

  1. Ordinations of the units, where interpoint distances optimally display the measured differences
  2. Clustering the units into homogeneous clusters
  3. Assessing differences between pre-specified groups of units (e.g. regions, periods, treatment–control groups)

In this video, Michael Greenacre introduces his new article, ‘‘Size’ and ‘Shape’ in the Measurement of Multivariate Proximity’, published in Methods in Ecology and Evolution, May 2017. In the context of species abundances, for example, he explains how much a chosen proximity measure captures the difference in “size” between two samples, i.e. difference in overall abundances, and differences in “shape”, i.e. differences in compositions or relative abundances.  He shows that the popular Bray-Curtis dissimilarity inevitably includes a part of the “size” difference in its measurement of multivariate proximity.

This video is based on the article ‘‘Size’ and ‘shape’ in the measurement of multivariate proximity‘ by Michael Greenacre.

Assessment of Stream Health with DNA Metabarcoding

Following on from last week’s press release ‘How Clean are Finnish Rivers?’, Vasco Elbrecht et al. have produced a video to explain the methods in ‘Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring‘.

In this video, the authors explore the potential of DNA metabarcoding to access stream health using macroinvertebrates. They compared DNA and morphology-based identification of bulk monitoring samples from 18 Finnish stream ecosystems. DNA-based methods show higher taxonomic resolution and similar assessment results as currently used morphology-based methods. Their study shows that the tested DNA-based methods integrate well with current approaches, but further optimisation and validation of DNA metabarcoding methods is encouraged.

This video is based on the article ‘Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring‘ by Elbrecht et al.

 

New Associate Editors

Today we are welcoming four new Associate Editors to Methods in Ecology and Evolution. Graziella Iossa (University of Lincoln) and Theoni Photopoulou (Nelson Mandela Metropolitan University) are joining as regular Associate Editors and Simon Jarman (Unversity of Porto) and Daniele Silvestro (University of Gothenburg) will be working on Applications articles. You can find out more about all of our new Associate Editors below.

Graziella Iossa

“I am an evolutionary ecologist with broad interests in behavioural and population ecology. My research has explored reproductive strategies and the evolution of male and female reproductive traits in mammals and insects and I have used a range of techniques to study the behaviour and welfare of wildlife. I have just started to explore interdisciplinary approaches with the aim to improve our understanding of the value and role of ecosystem services in human health, specifically for antimicrobial resistance.”

Graziella’s most recent paper – Micropyle number is associated with elevated female promiscuity in Lepidoptera – investigates the evolution of the micropyle, a tiny canal which sperm use to fertilise eggs in insects. This is the first study to show that micropylar variation is driven by female promiscuity – the more micropyles her eggs have, the more choice she is likely to have over which male fathers her offspring. Also, Graziella currently holds a NERC Valuing Nature placement which aims to combine perspectives from evolutionary ecology, microbial ecology, epidemiology, ecosystem science and public health to develop a new, holistic way of understanding antimicrobial resistance

Simon Jarman

“Methods employing epigenetics, environmental DNA analysis or bioinformatics for ecological research are improving rapidly and have clear potential for future development. My research focuses on creating new methods in these areas and using them to study population biology and biodiversity. Epigenetic markers for physiological features such as biological age can be used to determine key features of population biology such as age class distribution. Environmental DNA can be used to measure species distributions; biodiversity in environmental samples; and animal diet composition. I am interested in the molecular biology and computational approaches that are required to implement these methods; as well as how they can be used to study specific ecological questions.”

In November 2016, Simon published an Open Access article in Methods in Ecology and Evolution. ‘Optimised scat collection protocols for dietary DNA metabarcoding in vertebrates‘ explains how to collect scat samples to optimise the detection of food DNA in vertebrate scat samples. More recently, Simon was the last author of ‘KrillDB: A de novo transcriptome database for the Antarctic krill (Euphausia superba)‘ – which introduces the most advanced genetic database on Euphausia superba, KrillDB, and includes comprehensive data sets of former and present transcriptome projects.

Theoni Photopoulou

“I am interested in the way biological and ecological phenomena change in space and over time. My special interest is animal movement ecology and the mechanisms behind the patterns of movement we observe. Most of the time I work on ecological questions about how animals use their environment and the resources in it, using data collected remotely with animal-attached instruments. Marine biology was my first love so I will always have a soft spot for marine systems, especially movement of large marine vertebrates, but I work on all sorts of tracking data and also some non-tracking data.”

Theoni has also recently been published in Methods in Ecology and Evolution. Her article ‘Analysis of animal accelerometer data using hidden Markov model‘ appeared in the February issue of the journal (and provided the cover image). In the paper, the authors provide the details necessary to implement and assess a hidden Markov Model in both the supervised and unsupervised learning contexts and discuss the data requirements of each case. Another of Theoni’s articles has just been accepted for publication in Frontiers in Zoology. ‘Evidence for a postreproductive phase in female false killer whales (Pseudorca crassidens)‘ investigates the evidence for postreproductive lifespan (PRLS) in the false killer whale, using a quantitative measure of PRLS and morphological evidence from reproductive tissue.

Daniele Silvestro

“I am a computational biologist and my research focuses on (macro)evolution and the development of new probabilistic models to better understand it. I am interested in the implementation of Bayesian algorithms to model evolutionary processes such as phenotypic trait evolution and species diversification and extinction. I am also interested in historical biogeography and in particular in the estimation of dispersal rates and biotic connectivity between geographic areas. A lot of my work involves developing new models and algorithms and implementing them in computer programs. I have been using both phylogenetic data and fossil occurrences to infer deep time evolutionary dynamics and I am keen to see an improved integration between paleontological and neontological data in evolutionary research.”

In his most recent article – ‘Bayesian estimation of multiple clade competition from fossil data‘ – Daniele and his co-authors explore the properties of the existing Multiple Clade Diversity Dependence implementation, which is based on Bayesian variable selection, and introduce an alternative parameterisation based on the Horseshoe prior. He was also one of the authors of ‘Mammal body size evolution in North America and Europe over 20 Myr: similar trends generated by different processes‘, published in Proceedings of the Royal Society B earlier this year.

We are thrilled to welcome Simon, Graziella, Theoni and Daniele to the Associate Editor Board and we look forward to working with them over the coming years.

Issue 8.5

Issue 8.5 is now online!

The May issue of Methods is now online!

This issue contains three Applications articles and two Open Access articles. These five papers are freely available to everyone, no subscription required.

MatlabHTK: A software interface to a popular speech recognition system making it possible for non-experts to implement hidden Markov models for bioacoustic signal processing.

 PrimerMiner: The R package PrimerMiner batch downloads DNA barcode gene sequences from BOLD and NCBI databases for specified target taxonomic groups and then applies sequence clustering into operational taxonomic units to reduce biases introduced by the different number of available sequences per species.

 BarcodingR: An integrated software package that provides a comprehensive implementation of species identification methods, including artificial intelligence, fuzzy-set, Bayesian and kmer-based methods, that are not readily available in other packages.

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Digitizing Historical Land-use Maps with HistMapR

Habitat destruction and degradation represent serious threats to biodiversity, and quantification of land-use change over time is important for understanding the consequences of these changes to organisms and ecosystem service provision.

Historical land-use maps are important for documenting how habitat cover has changed over time, but digitizing these maps is a time consuming process. HistMapR is an R package designed to speed up the digitization process, and in this video we take an example map to show you how the method works.

Digitization is fast, and agreement with manually digitized maps of around 80–90% meets common targets for image classification. We hope that the ability to quickly classify large areas of historical land use will promote the inclusion of land-use change into analyses of biodiversity, species distributions and ecosystem services.

This video is based on the Applications article ‘HistMapR: Rapid digitization of historical land-use maps in R‘ by Auffret et al. This article is freely available to anyone (no subscription required).

The package is hosted on GitHub and example scripts can be downloaded from Figshare.